相关论文: Classification of 4XMM-DR9 Sources by Machine Lear…

Machine learning has emerged as a powerful tool in the field of gamma-ray astrophysics. The algorithms can distinguish between different source types, such as blazars and pulsars, and help uncover new insights into the high-energy universe.…

The CFHTLS presents a unique data set for weak lensing studies, having high quality imaging and deep multi-band photometry. We have initiated an XMM-CFHTLS project to provide X-ray observations of the brightest X-ray selected clusters…

We present a galaxy cluster survey based on XMM-Newton observations that are located in Stripe 82 of the Sloan Digital Sky Survey (SDSS). The survey covers an area of 11.25 deg$^2$. The X-ray cluster candidates were selected as…

The XMM identification programme (XID) is accumulating Optical/IR images and spectra to identify thousands of XMM sources. The XID Database is the main repository of this data and permits easy selection and correlation of XMM X-ray and UV…

We present an X-ray point-source catalog from the XMM-Large Scale Structure survey region (XMM-LSS), one of the XMM-Spitzer Extragalactic Representative Volume Survey (XMM-SERVS) fields. We target the XMM-LSS region with $1.3$ Ms of new…

We present the X-ray source detection procedure that we have developed for the purpose of assembling and characterizing controlled samples of cluster of galaxies for the XMM Large Scale Structure Survey. We describe how we model the…

The XMM Cluster Survey (XCS) is a serendipitous search for galaxy clusters using all publicly available data in the XMM-Newton Science Archive. Its main aims are to measure cosmological parameters and trace the evolution of X-ray scaling…

We present a convolutional neural network to classify distinct cosmological scenarios based on the statistically similar weak-lensing maps they generate. Modified gravity (MG) models that include massive neutrinos can mimic the standard…

Population studies of the extragalactic objects are a major part of the universe large-scale structure study. Apart from radio, infrared, and visible wavelength bands, observations and further identification of extragalactic objects such as…

Machine learning techniques have been increasingly useful in astronomical applications over the last few years, for example in the morphological classification of galaxies. Convolutional neural networks have proven to be highly effective in…

[ABRIGED] We present the optical identification of a sample of 695 X-ray sources detected in the first 1.3 deg^2 of the XMM-COSMOS survey, down to a 0.5-2 keV (2-10 keV) limiting flux of ~10^-15 erg cm-2 s-1 (~5x10^-15 erg cm^-2 s-1). We…

Many open questions in X-ray astronomy are limited by the relatively small number of objects in uniform optically-identified samples, especially when rare subclasses are considered, or subsets isolated to search for evolution or…

The radio-quiet neutron star 1E1207.4-5209 has been the target of several XMM-Newton observations, with a total exposure of ~350 ks. The source is located at intermediate galactic latitude (b~10 degrees), i.e. in a sky region with an…

Knowing the redshift of galaxies is one of the first requirements of many cosmological experiments, and as it's impossible to perform spectroscopy for every galaxy being observed, photometric redshift (photo-z) estimations are still of…

Classification will be an important first step for upcoming surveys that will detect billions of new sources such as LSST and Euclid, as well as DESI, 4MOST and MOONS. The application of traditional methods of model fitting and…

The latest $\textit{Fermi}$-LAT gamma-ray catalog, 4FGL-DR3, presents a large fraction of sources without clear association to known counterparts, i.e., unidentified sources (unIDs). In this paper, we aim to classify them using machine…

The XMM-Newton spectral-fit database (XMMFITCAT) is a catalogue of spectral fitting results for the source detections within the XMM-Newton Serendipitous source catalogue with more than 50 net (background-subtracted) counts per detector in…

We present a catalogue of X-ray selected galaxy clusters and groups as a first release of the 2XMMi/SDSS Galaxy Cluster Survey. The survey is a search for galaxy clusters detected serendipitously in observations with XMM-Newton in the…

We investigate star-galaxy classification for astronomical surveys in the context of four methods enabling the interpretation of black-box machine learning systems. The first is outputting and exploring the decision boundaries as given by…

Our survey of the fourth $\mathit{Fermi}$ Large Area Telescope catalog (4FGL) unassociated gamma-ray source regions using the X-Ray Telescope (XRT) and Ultraviolet/Optical Telescope (UVOT) aboard the Neil Gehrels $\mathit{Swift}$…